Skip to content
Archive
← r/algotrading
1
100%
u/1ncehost 3 days ago Strategy

Various high performing switchboards OOS last year

I'm one of the top creators on Composer with hundreds of portfolios using my public algos (search for Curved). I have many private ones also and figured I'd dump some high performing ones here. The 3-15 year backtests (some rely on newer symbols) on these are also exceptionally high. Having watched this sub for some time, I suspect comments will be full of suspicion. The suspicion is justified, but you are welcome to look up the public ones if curious. I think the biggest criticisms should be that its unknown whether these algos are regime based, and also how much they can scale, given they collectively have only about one year OOS and unknown AOM. I think its likely they benefit from small inefficiencies that generally won't scale, but I long date backtest, and take measures to prevent survivorship bias, so I am generally confident they are not regime based. I design for low market and inter-sleeve correlation, so you'd want to run these rebalancing against other sleeves to maximize actual performance anyway. I personally am suspicious of composer, so I reimplemented composer's execution system and run these and about 30 more algos on my own server with my own funds and have representative results. In addition to composer switchboards, I also run some other types of algos to rebalance against, but I personally am a fan of switchboards because the determinism adds a layer of assurance, and daily or longer trading intervals increasingly disarm adverse selection bias. I perform a lot of signal research, some automated, and use highly non-traditional methodology to select signals. Generally I believe that the non traditional signal selection is why I find systemic market inefficiencies that others miss. Traditionalism can be said to be a risk aversion bias which classically trained and corporate algo researchers have, and I believe my methodologies generally exploit this bias. That's a slippery slope because most non-traditional ideas are not sound, but what I'm saying is that not all traditional ideas are sound either, and I think that is especially true with game theory included. Anyway, if any of this was interesting to you, I'd be interested in hearing your critiques, thoughts, or questions. I know it might come off as a brag, but thats just my autism showing. Its more supposed to be a conversation starter, and I am genuintely curious if anyone spends time thinking about the biases I mentioned.
19 comments held Reddit says 0 on reddit ↗
  1. u/Enough_Effective7176 1 3 days ago
    So where are the strats and results?
  2. u/1ncehost OP 1 3 days ago
    Search Curved on Composer for some. Some are private. These are OOS results, not backtests.
  3. u/jnwatson 1 3 days ago
    Looking at your algos, they are legit, because they are macro focused. You are making smart medium term investment decisions and encoding them in your algos. Going long semi in 2025 was a great call, regardless of the algo. Going long China stocks the same. The real question is whether your algo improves over the basket you rotate through. You might just be good at stock picking, which is a good problem to have.
  4. u/1ncehost OP 1 3 days ago
    I have a couple which are based on macro picks like that, but most are based on various hopefully-cycle-agnostic macro signals. For instance this one: https://app.composer.trade/watch?factshee… You may see SOXL and assume its a sector pick, but its actually picked because of all sectors, semis are causally correlated with short term changes to high yield debt rates as represented by HYG RSI. Most of my algos are based on signals like that.
  5. u/jnwatson 1 3 days ago
    There's a valid thesis in there, but it ends up just being 70% SPY with extra drawdown. Another point in your favor is it doesn't look overfit like most of the leader strategies in Composer are.
  6. u/Loose-Loss-7215 1 3 days ago
    These are backtests with no real results? Where is the slippage and missed trades that happen when you go live?
  7. u/1ncehost OP 1 3 days ago
    These are all OOS as the title says, not backtests
  8. u/[deleted] 1 3 days ago

    [removed] — already gone when the archive first saw it

  9. u/ReporterCalm6238 1 3 days ago
    1) this sounds like an ad for Composer 2) why backtested only on 2025? 3) why no live paper trading results? 4) how do you know that this is not overfitting?
  10. u/1ncehost OP 1 3 days ago
    These aren't backtests, these are OOS. The backtests go back many years.
  11. u/stereotomyalan 1 3 days ago
    Is the yellow dashed line the return line? if so, it's perfect
  12. u/1ncehost OP 1 3 days ago
    The yellow line is clearly labeled in the graph as SPY
  13. u/Many-Pick5066 1 3 days ago
    the thread is arguing about whether these are backtests or forward results and thats the less interesting question. take the OOS claim at face value. the problem is which ones youre showing. you have the public ones, many private ones, and about thirty more on your own server. what got posted is the high performers over the same twelve months. that year did the picking, so for the set as posted its not out of sample anymore. it was out of sample per algo, and you spent it choosing between them. the survivorship measures dont cover this. those handle symbols leaving a universe. this is selection across strategies and it survives clean symbol handling completely intact. you already have the fix sitting on your server. show the whole population over that year instead of the top slice. if the median switchboard beat its benchmark thats a much stronger claim than any single curve, and if the median is flat then the good ones are the tail youd get from that many draws whatever the signal work was worth. at daily or longer rebalance a year is a small number of independent decisions to be ranking that many candidates on.
  14. u/dazuma 1 3 days ago
    Ai slop
  15. u/1ncehost OP 1 3 days ago
    This is the right direction in my opinion. If one is trying to know whether I have anything worth paying attention to, the first question should be whether results are real, and assuming I'm telling the truth, you identified most of the attributes that need to be checked. The truth is I don't have clean whole portfolio data yet for various reasons: 1) I've migrated to my custom environment during this timeframe and changed attributes I haven't tracked well 2) I let algorithms run OOS for a while before running them live 3) Variance between simulated OOS and actual execution is dramatic for many signals (small input changes produce large effects). I can tell you that in my custom environment, my real money whole portfolio gain is currently annualized 81% with 12% max drawdown since the beginning of April until this week. This number includes the losers. I don't think this is a meaningful result yet, and expect it to be worse over time, but it is a positive indicator. Ultimately I'm not trying to stand up and say I'm the expert you should listen to, I'm just talking about some algorithms I made and chat about techniques if anyone is interested.
  16. u/HugeAd1329 1 3 days ago
    If you ran a shitload is Strats “OOS” and only showed the ones that were profitable OOS then they are no longer OOS, they are in sample.
  17. u/Sporkers 1 2 days ago
    This, if you made 100 strategies on Composer ran them all OOS and then are showing using 5 that did awesome the last 6 months or whatever, that was bound to happen with that kind of sample and cherry picking.
  18. u/Effective_Manager273 1 2 days ago
    you preempted the main criticism yourself, which is fair, so the useful question is what would make the OOS year convincing rather than suggestive. one year of live is roughly what, 250 observations, and if the switching logic only fires a handful of times then your effective sample is the number of switches, not the number of days. i would want to see the count of regime flips over that year. four flips that all worked is not evidence yet, it is four coin flips. the thing i would check on the scaling worry is the participation rate on the days the switchboard rotates. if the rotation days cluster on high volume names you are probably fine, if they cluster on thin ones your backtest fills are fiction at any real size. also worth separating: how much of the OOS return came from the switching versus from just being long the strongest sleeve the whole time. a static equal weight of the same sleeves is the benchmark that matters, not SPY.
  19. u/Grand-Fly-6090 1 2 days ago
    Couldn’t find any intra day strategies.